Imputation methods for missing outcome data in meta-analysis of clinical trials

Julian P T Higgins, Ian R White, Angela M Wood

Research output: Contribution to journalArticle (Academic Journal)peer-review

202 Citations (Scopus)

Abstract

Missing outcome data from randomized trials lead to greater uncertainty and possible bias in estimating the effect of an experimental treatment. An intention-to-treat analysis should take account of all randomized participants even if they have missing observations.
Original languageEnglish
Pages (from-to)225-39
Number of pages15
JournalClinical Trials
Volume5
Issue number3
DOIs
Publication statusPublished - 2008

Keywords

  • Schizophrenia
  • Haloperidol
  • Uncertainty
  • Randomized Controlled Trials as Topic
  • Humans
  • Outcome Assessment (Health Care)
  • Models, Statistical
  • Research Design
  • Meta-Analysis as Topic

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